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研究检索external-servicegithub未标认证来源可访问clear审计通过

pyroscopepyroscope 搜索

Agent Skill

pyroscope 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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周安装

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下载量

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CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:pyroscope(pyroscope 搜索)
来源仓库:https://github.com/julianobarbosa/claude-code-skills
仓库路径:skills/pyroscope
安装命令:
npx skills add https://github.com/julianobarbosa/claude-code-skills --skill pyroscope
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/julianobarbosa/claude-code-skills --skill pyroscope

简介

pyroscope 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词快速定位候选结果时使用。

  • 适用于研究检索类任务,支持基于关键词、任务场景或来源线索进行信息筛选。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装,需确认权限范围和是否触发联网操作。
  • 安装前建议核实仓库维护状态及是否会执行命令或读写文件,避免误改数据。
  • 可结合原始 README 进一步核验具体用法和功能边界。

SKILL.md

Grafana Pyroscope Skill

Comprehensive guide for Grafana Pyroscope - the open-source continuous profiling platform for analyzing application performance at the code level.

What is Pyroscope?

Pyroscope is a horizontally-scalable, highly-available, multi-tenant continuous profiling system that:

  • Collects profiling data continuously with minimal overhead (~2-5% CPU)
  • Provides code-level visibility with source-line granularity
  • Stores compressed profiles in object storage (S3, GCS, Azure Blob)
  • Integrates with Grafana for correlating profiles with metrics, logs, and traces
  • Supports multiple languages - Go, Java, Python,.NET, Ruby, Node.js, Rust

Architecture Overview

Core Components

ComponentPurpose
DistributorValidates and routes incoming profiles to ingesters
IngesterBuffers profiles in memory, compresses and writes to storage
QuerierRetrieves and processes profile data for analysis
Query FrontendHandles query requests, caching, and scheduling
Query SchedulerManages per-tenant query queues
Store GatewayProvides access to long-term profile storage
CompactorMerges blocks, manages retention, handles deletion

Data Flow

Write Path:

SDK/Alloy → Distributor → Ingester → Object Storage
                                   ↓
                             Blocks + Indexes

Read Path:

Query → Query Frontend → Query Scheduler → Querier
                                             ↓
                                    Ingesters + Store Gateway

Deployment Modes

1. Monolithic Mode (-target=all)

  • All components in single process
  • Best for: Development, small-scale deployments
  • Query URL: http://pyroscope:4040/

2. Microservices Mode (Production)

  • Each component runs independently
  • Horizontally scalable
  • Query URL: http://pyroscope-querier:4040/
# Microservices deployment
architecture:
  microservices:
    enabled: true

querier:
  replicas: 3
distributor:
  replicas: 2
ingester:
  replicas: 3
compactor:
  replicas: 3
storeGateway:
  replicas: 3

Quick Start - Kubernetes Helm

Add Repository

helm repo add grafana https://grafana.github.io/helm-charts
helm repo update

Install Single Binary

kubectl create namespace pyroscope
helm install pyroscope grafana/pyroscope -n pyroscope

Install Microservices Mode

curl -Lo values-micro-services.yaml \
  https://raw.githubusercontent.com/grafana/pyroscope/main/operations/pyroscope/helm/pyroscope/values-micro-services.yaml

helm install pyroscope grafana/pyroscope \
  -n pyroscope \
  --values values-micro-services.yaml

Profile Types

TypeDescriptionLanguages
CPUWall/CPU time consumptionAll
MemoryAllocation objects/space, heapGo, Java,.NET
GoroutineConcurrent goroutinesGo
MutexLock contention (count/duration)Go, Java,.NET
BlockThread blocking/delaysGo
ExceptionsException trackingPython

Client Configuration Methods

Method 1: SDK Instrumentation (Push Mode)

Go SDK:

import "github.com/grafana/pyroscope-go"

pyroscope.Start(pyroscope.Config{
    ApplicationName: "my-app",
    ServerAddress:   "http://pyroscope:4040",
    ProfileTypes: []pyroscope.ProfileType{
        pyroscope.ProfileCPU,
        pyroscope.ProfileAllocObjects,
        pyroscope.ProfileAllocSpace,
        pyroscope.ProfileInuseObjects,
        pyroscope.ProfileInuseSpace,
        pyroscope.ProfileGoroutines,
        pyroscope.ProfileMutexCount,
        pyroscope.ProfileMutexDuration,
        pyroscope.ProfileBlockCount,
        pyroscope.ProfileBlockDuration,
    },
    Tags: map[string]string{
        "env": "production",
    },
})

Java SDK:

PyroscopeAgent.start(
    new Config.Builder()
        .setApplicationName("my-app")
        .setServerAddress("http://pyroscope:4040")
        .setProfilingEvent(EventType.ITIMER)
        .setFormat(Format.JFR)
        .build()
);

Python SDK:

import pyroscope

pyroscope.configure(
    application_name="my-app",
    server_address="http://pyroscope:4040",
    tags={"env": "production"},
)

Method 2: Grafana Alloy (Pull Mode)

Auto-instrumentation via Annotations:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-app
spec:
  template:
    metadata:
      annotations:
        profiles.grafana.com/cpu.scrape: "true"
        profiles.grafana.com/cpu.port: "8080"
        profiles.grafana.com/memory.scrape: "true"
        profiles.grafana.com/memory.port: "8080"
        profiles.grafana.com/goroutine.scrape: "true"
        profiles.grafana.com/goroutine.port: "8080"

Alloy Configuration:

pyroscope.scrape "default" {
  targets = discovery.kubernetes.pods.targets
  forward_to = [pyroscope.write.default.receiver]

  profiling_config {
    profile.process_cpu { enabled = true }
    profile.memory { enabled = true }
    profile.goroutine { enabled = true }
  }
}

pyroscope.write "default" {
  endpoint {
    url = "http://pyroscope:4040"
  }
}

Method 3: eBPF Profiling (Linux)

For compiled languages (C/C++, Go, Rust):

pyroscope.ebpf "default" {
  forward_to = [pyroscope.write.default.receiver]
  targets = discovery.kubernetes.pods.targets
}

Storage Configuration

Azure Blob Storage

pyroscope:
  config:
    storage:
      backend: azure
      azure:
        container_name: pyroscope-data
        account_name: mystorageaccount
        account_key: ${AZURE_ACCOUNT_KEY}

AWS S3

pyroscope:
  config:
    storage:
      backend: s3
      s3:
        bucket_name: pyroscope-data
        region: us-east-1
        endpoint: s3.us-east-1.amazonaws.com
        access_key_id: ${AWS_ACCESS_KEY_ID}
        secret_access_key: ${AWS_SECRET_ACCESS_KEY}

Google Cloud Storage

pyroscope:
  config:
    storage:
      backend: gcs
      gcs:
        bucket_name: pyroscope-data
        # Uses GOOGLE_APPLICATION_CREDENTIALS

Grafana Integration

Data Source Configuration

apiVersion: 1
datasources:
  - name: Pyroscope
    type: grafana-pyroscope-datasource
    access: proxy
    url: http://pyroscope-querier:4040
    isDefault: false
    editable: true

Trace-to-Profile Linking

Enable span profiles to correlate traces with profiles:

Go with OpenTelemetry:

import (
    "github.com/grafana/pyroscope-go"
    otelpyroscope "github.com/grafana/otel-profiling-go"
)

tp := trace.NewTracerProvider(
    trace.WithSpanProcessor(otelpyroscope.NewSpanProcessor()),
)

Requirements:

  • Minimum span duration: 20ms
  • Supported: Go, Java,.NET, Python, Ruby

Resource Requirements

Single Binary (Development)

resources:
  requests:
    cpu: 500m
    memory: 512Mi
  limits:
    cpu: 1
    memory: 2Gi

Microservices (Production)

ComponentCPU RequestMemory RequestMemory Limit
Distributor500m256Mi1Gi
Ingester18Gi16Gi
Querier100m256Mi1Gi
Query Frontend100m256Mi1Gi
Compactor18Gi16Gi
Store Gateway18Gi16Gi

Common Helm Values

# Production values
architecture:
  microservices:
    enabled: true

pyroscope:
  persistence:
    enabled: true
    size: 50Gi

  config:
    storage:
      backend: s3
      s3:
        bucket_name: pyroscope-prod
        region: us-east-1

# High availability
ingester:
  replicas: 3
  terminationGracePeriodSeconds: 600

querier:
  replicas: 3

distributor:
  replicas: 2

compactor:
  replicas: 3
  terminationGracePeriodSeconds: 1200

storeGateway:
  replicas: 3

# Pod disruption budget
podDisruptionBudget:
  enabled: true
  maxUnavailable: 1

# Topology spread
topologySpreadConstraints:
  - maxSkew: 1
    topologyKey: kubernetes.io/hostname
    whenUnsatisfiable: DoNotSchedule

# Monitoring
serviceMonitor:
  enabled: true

# Alloy for profile collection
alloy:
  enabled: true

API Endpoints

Ingestion

# Push profiles (Connect API)
POST /push.v1.PusherService/Push

# Legacy HTTP (pprof, JFR formats)
POST /ingest

Query

# Merged profile
POST /querier.v1.QuerierService/SelectMergeProfile

# Flame graph data
POST /querier.v1.QuerierService/SelectMergeStacktraces

# Available labels
POST /querier.v1.QuerierService/LabelNames

# Profile types
POST /querier.v1.QuerierService/ProfileTypes

# Legacy render
GET /pyroscope/render?query={}&from=now-1h&until=now

System

# Readiness
GET /ready

# Configuration
GET /config

# Metrics
GET /metrics

Troubleshooting

Diagnostic Commands

# Check pod status
kubectl get pods -n pyroscope -l app.kubernetes.io/name=pyroscope

# View ingester logs
kubectl logs -n pyroscope -l app.kubernetes.io/component=ingester --tail=100

# Check ring status
kubectl exec -it pyroscope-0 -n pyroscope -- \
  curl http://localhost:4040/ingester/ring

# Verify readiness
kubectl exec -it pyroscope-0 -n pyroscope -- \
  curl http://localhost:4040/ready

# Check configuration
kubectl exec -it pyroscope-0 -n pyroscope -- \
  curl http://localhost:4040/config

Common Issues

1. Ingester OOM:

ingester:
  resources:
    limits:
      memory: 16Gi

2. Storage Authentication Failed:

# Azure - verify RBAC
az role assignment create \
  --role "Storage Blob Data Contributor" \
  --assignee-object-id <principal-id> \
  --scope <storage-scope>

3. High Cardinality Labels:

# Limit label cardinality
pyroscope:
  config:
    validation:
      max_label_names_per_series: 25

4. Query Timeout:

pyroscope:
  config:
    querier:
      query_timeout: 5m
      max_concurrent: 8

Reference Documentation

For detailed configuration by topic:

External Resources

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

27.75%
按下载量换算96

Gemini CLI

24.54%
按下载量换算85

Cursor

15.73%
按下载量换算54

OpenCode

12.83%
按下载量换算44

Antigravity

7.24%
按下载量换算25

Codex

3.58%
按下载量换算12

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。

来源信息

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